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Doctor–medical institution collaboration (DMIC) services are an emerging service mode in focal online health communities (OHCs). This new service mode is anticipated to affect user satisfaction and doctors' engagement behaviors. However, whether and how DMIC occurs is still ambiguous because the topic is rarely examined. To bridge this gap, this study explores doctors' participation in DMIC services and its effects on their online performance, as well as its effect on patients' evaluation of them on OHC platforms.

The authors propose hypotheses based on structural holes theory. A unique dataset obtained from one of the most popular OHCs in China is used to test the hypotheses, and difference-in-differences estimation is adopted to test the causality of the relationship.

The results demonstrate that providing DMIC services improves doctors' online consultation performance and patients' evaluations of them but has no significant effect on doctors' knowledge-sharing performance on OHC platforms. Doctors' knowledge-sharing performance and consultation performance mediate the relationship between participation in DMIC services and patients' evaluation of doctors. Regarding doctors' participation in DMIC services, its impact on doctors' consultation performance and patients' evaluation of them is weaker for doctors with higher professional titles than for doctors with lower professional titles.

The findings clarify the value creation mechanisms of online collaboration between doctors and medical institutions and thereafter facilitate doctors' participation in DMIC services and enhance the sustainable development of OHCs.

This paper aims to explore the impacts of the recent development of Korean free trade agreements (FTAs) on its seaborne trade volumes. The paper firstly estimates the changes in cargo value flows caused by Korea-EU FTA, Korea-USA FTA and Korea-ASEAN FTA using a global computable general equilibrium model named Global Trade Analysis Project (GTAP) and its most recent database - version 7 with 2004 as the base year. Then a set of systematic conversion factors transferring trade value flows to volume flows of different types of commodities is calibrated according to the United Nations COMTRADE database and is used to convert the GTAP trade value flows into volume flows. Having indentified maritime cargo flows by different commodity types, this paper attempts to draw implications for maritime logistics policy in order to facilitate the trade of Korean merchandises and to propose key competitive strategy for the maritime container transport networking and logistics service providers in the Korean logistics industry.

The purpose of this study is to improve the accuracy of a fused deposition modeling three-dimensional (3D) printer by identifying and compensating for position-independent geometric errors using a face-diagonal length test featuring a designed artifact and a Vernier caliper.

An artifact that does not require support when printing was designed and printed to allow performance of the face-diagonal length test. A Vernier caliper was used to measure the lengths of diagonals in the XY, YZ and ZX planes of the printed artifact specimen; this completed the face-diagonal length test. The relationships between position-independent geometric errors of the linear axes X, Y and Z and the measured diagonal lengths of the three planes were determined to identify geometric errors.

The approach was applied to a commercial fused deposition modeling 3D printer, and three position-independent geometric errors were rapidly identified. The artifact was re-printed after model-based compensation for these errors and the diagonal lengths were re-measured. The results were verified via coordinate measuring machine measurement of a simple test piece without and with model-based compensation for identified geometric errors. Furthermore, the proposed approach was applied to a commercial 3D printer.

The measured diagonal lengths of the printed artifacts varied greatly. Thus, further studies should investigate the effects of printing materials and parameters on the length discrepancies of 3D printed artifacts.

A software-based compensation of identified position-independent geometric errors has to be used at commercial 3D printers for accuracy improvements of printed parts.

Thus, the approach is of practical utility; it can be periodically used to identify position-independent geometric errors and ensure that the 3D printer is consistently accurate.

The aim of this study was to analyze the effects of carbon reduction efforts and preservation efforts on system benefits in the cold chain industry of fresh products.

This study develops an optimal decision game model for the fresh products in the cold chain, incorporating the retailer's preservation effort and the supplier's carbon emission reduction effort. It quantifies the relationship between carbon emission reduction effort, preservation effort and system profit. The model considers parameters like carbon trading price, consumer low-carbon preference and consumer freshness preference, reflecting real-world conditions and market trends. Numerical simulations are conducted by varying these parameters to observe their impact on system profit.

Under the carbon cap-and-trade policy, the profit of the fresh cold chain system is higher than that of the fresh cold chain system without carbon constraints, and the profit of the supplier under decentralized decision-making is increased by nine times in the simulation results. The increase in carbon trading prices can effectively improve the freshness level of fresh products cold chain, carbon emission reduction level and system profit.

This study comprehensively considers the factors of freshness and carbon emission reduction, provides the optimal low-carbon production decision-making reference for the fresh food cold chain and promotes the sustainable development of the fresh food cold chain.

Modelling and forecasting interval-valued time series (ITS) have received increasing attention in statistics and econometrics. An interval-valued observation contains more information than a point-valued observation in the same time period. The previous literature has mainly considered modelling and forecasting a univariate ITS. However, few works attempt to model a vector process of ITS. In this paper, we propose an interval-valued vector autoregressive moving average (IVARMA) model to capture the cross-dependence dynamics within an ITS vector system. A minimum-distance estimation method is developed to estimate the parameters of an IVARMA model, and consistency, asymptotic normality and asymptotic efficiency of the proposed estimator are established. A two-stage minimum-distance estimator is shown to be asymptotically most efficient among the class of minimum-distance estimators. Simulation studies show that the two-stage estimator indeed outperforms other minimum-distance estimators for various data-generating processes considered.

In recent years, we have witnessed a surge in academic interest towards migrants and their entrepreneurial endeavours. This has resulted in valuable insights about immigrant, transnational, ethnic and diaspora entrepreneurship. By reviewing 158 articles published in the fields of migrant entrepreneurship, transnational entrepreneurship, ethnic and diaspora entrepreneurship over the last decade, the author maps the migrant entrepreneurship field according to the level of analysis and suggests potential avenues for the development of the field. Blurred boundaries between different streams of literature can potentially lead to duplication of efforts and harm cumulativity of knowledge. Therefore, the author summarises the key findings at each level of analysis, identifies the gaps and most pressing research questions. The author concluded that the field would benefit from (1) more specific definitions and assessment of whether observed findings stem from immigrant-, transnational-, ethnic- or diaspora-related factors; (2) appreciating the multilevel nature of the phenomenon; and (3) clarifying the boundary conditions. This review contributes to the accumulation of knowledge in two ways. First, it synthesises the findings in the fields of transnational, immigrant, ethnic and diaspora entrepreneurship under the framework of migrant entrepreneurship. Second, it suggests potential research directions across three levels of analysis and in-between those levels.

Based on the background of enterprise digital transformation, this paper aims to examine the impact of digitization on the cooperative behavior and environmental performance of green technology innovation.

By constructing a model of quantity competition between the two enterprises, this paper examines the impact of digitization on the cooperative behavior and environmental performance of green technology innovation from the micro level. It uses Shanghai and Shenzhen A-share-listed companies as research samples. An unbalanced panel data set from 2011 to 2018 was constructed to empirically test the effect of digital transformation on the environmental performance of enterprises.

The findings reveal the following. First, digital transformation can significantly improve the environmental performance of enterprises. Second, green technological innovation sharing plays an intermediary role between digital transformation and enterprise environmental performance. Third, when the level of digitization is high, the sharing effect of green technology innovation brought about by digital technology is stronger and enterprises tend to carry out cooperative green technology innovation. Lastly, the level of development of regional science and technology finance plays a positive regulatory role in digital transformation and enterprise environmental performance.

This paper first proposes that green technology innovation-sharing is an important mechanism that can significantly improve enterprises' environmental performance. The authors empirically examine the mechanism and analyze the heterogeneity of the impact of digitalization level on enterprises' environmental performance. The authors also discuss the moderating effect of regional technology and finance development levels on the relationship between digitalization and enterprises' environmental performance.

Purpose – The purpose of the research was to examine the process of new teacher evaluation policy development in South Korea, in order to gain insight into how a controversial policy could be established in education. Research questions were about the process of the policy development, political actors involved and their influences, and the meaning of teacher evaluation in the newly established teacher evaluation policy.Methodology – The study uses a qualitative and descriptive-analytical process from a hermeneutics perspective that views policy as text to be interpreted. This perspective allows policy to be connected to a larger social context through interpretations of text. The main data sources included policy documents, statements by various organizations, research reports, and public media artifacts produced between 2000 and 2012. For data analysis, constant comparison and content analysis methods were used.Findings – The findings show that the process of developing a teacher evaluation system demonstrated an unsuccessful attempt to apply the Habermasian notion of discursive democracy. Relevant stakeholders were invited to deliberate on the reform, but official meetings ended prematurely without consensus. In the end, the government proceeded without full support of any stakeholders. During the deliberation process, teacher organizations and parent groups demonstrated conflicting perspectives on teacher work and the new evaluation system only partially accommodated both perspectives. The effectiveness of the new evaluation system remains to be researched.Value – The policy development process and the evaluation system shown in this study should inform similar efforts in other contexts.

Purpose – This study explored how the pandemic shaped or shifted legacy news reporting about crime, focusing on Twitter posts as visual elements of the crossmedia landscape.

Methodology/Approach – Drawing a purposive sample of tweets about crime and the pandemic posted from March 2020 to December 2021 by major TV news outlets, the qualitative media analysis (QMA) scrutinized how tweets constructed narratives about crime. The analysis considered images, text, and their juxtaposition within tweets and over time.

Findings – This study found that news organizations partnered the pandemic and crime in the American discourse of fear. Tweets acted as crime news snapshots, which magnified a sense of instability and uncertainty. Tweets constructed a collective malaise that could contribute to users’ sense of ontological insecurity.

Originality/Value – The spectacle of crime churned through news organizations’ tweets, dissociating crime from the complex social context of the pandemic. Attention to the liquidity of images and information in the crossmedia landscape revealed fluctuating social meanings and disorientation.